Infancy and childhood growth and physical activity in adolescence: prospective birth cohort study from Brazil.

BACKGROUND: The Developmental Origins of Health and Disease hypothesis suggests that intrauterine, infancy and early childhood variables play a key role at programming later health. However, little is known on the programming of behavioral variables, because most studies so far focused on chronic disease-related and human capital outcomes. The aim of the present study was to evaluate the effects of prenatal, infancy and childhood weight and length/height gains on objectively-measured physical activity (PA) in adolescence. METHODS: This is a prospective birth cohort study in Pelotas, Brazil, including 457 adolescents (mean age: 13.3 years) with weight and length/height data at birth, one, three and six months, one and four years of age. PA was measured using a GT1M Actigraph accelerometer, and expressed as (a) minutes per day spent on sedentary, light, moderate, vigorous and very-vigorous activities; (b) total counts per day. RESULTS: 61.3% of the adolescents accumulated 60+ minutes of moderate-to-vigorous PA per day. Weight and length/height trajectories in infancy and childhood were similar between those classified as active or inactive at 13.3 years. However, those classified as inactive were heavier and taller at all ages; differences were statistically significant only in terms of length at three, six and 12 months. CONCLUSIONS: Weight gain in infancy and childhood did not predict variability in adolescent PA, but those active in adolescence showed somewhat smaller average gains in length in infancy. These findings suggest that PA may partially be sensitive to early hormonal programming, or that genetic factors may affect both early growth and later metabolism or predisposition for PA.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Moving the needle: Employing deep reinforcement learning to push the boundaries of coarse-grained vaccine models

Highly mutable infectious disease pathogens (hm-IDPs) such as HIV and influenza evolve faster than the human immune system can contain them, allowing them to circumvent traditional vaccination approaches and causing over one million deaths annually. Agent-based models can be used to simulate the complex interactions that occur between immune cells and hm-IDP-like proteins (antigens) during affinity maturation&mdash;the process by which antibodies evolve. Compared to existing experimental approaches, agent-based models offer a safe, low-cost, and rapid route to study the immune response to vaccines spanning a wide range of design variables. However, the highly stochastic nature of affinity maturation and vast sequence space of hm-IDPs render brute force searches intractable for exploring all pertinent vaccine design variables and the subset of immunization protocols encompassed therein. To address this challenge, we employed deep reinforcement learning to drive a recently developed agent-based model of affinity maturation to focus sampling on immunization protocols with greater potential to improve the chosen metrics of protection, namely the broadly neutralizing antibody (bnAb) titers or fraction of bnAbs produced. Using this approach, we were able to coarse-grain a wide range of vaccine design variables and explore the relevant design space. Our work offers new testable insights into how vaccines should be formulated to maximize protective immune responses to hm-IDPs and how they can be minimally tailored to account for major sources of heterogeneity in human immune responses and various socioeconomic factors. Our results indicate that the first 3 to 5 immunizations, depending on the metric of protection, should be specially tailored to achieve a robust protective immune response, but that beyond this point further immunizations require only subtle changes in formulation to sustain a durable bnAb response. &nbsp;</p

Reassessing Ethnic Differences in Mean BMI and Changes Between 2007 and 2013 in English Children.

OBJECTIVE: National body fatness (BF) data for English South Asian and Black children use BMI, which provides inaccurate ethnic comparisons. BF levels and time trends in the English National Child Measurement Programme (NCMP) between 2007 and 2013 were assessed by using ethnic-specific adjusted BMI (aBMI) for South Asian and Black children. METHODS: Analyses were based on 3,195,323 children aged 4 to 5 years and 2,962,673 children aged 10 to 11 years. aBMI values for South Asian and Black children (relating to BF as in White children) were derived independently. Mean aBMI levels and 5-year aBMI changes were obtained by using linear regression. RESULTS: In the 2007-2008 NCMP, mean aBMIs in 10- to 11-year-old children (boys, girls) were higher in South Asian children (20.1, 19.9 kg/m2 ) and Black girls, but not in Black boys (18.4, 19.2 kg/m2 ) when compared with White children (18.6, 19.0 kg/m2 ; all P < 0.001). Mean 5-year changes (boys, girls) were higher in South Asian children (0.16, 0.32 kg/m2 per 5 y; both P < 0.001) and Black boys but not girls (0.13, 0.15 kg/m2 per 5 y; P = 0.01, P = 0.41) compared with White children (0.02, 0.11 kg/m2 per 5 y). Ethnic differences at 4 to 5 years were similar. Unadjusted BMI showed similar 5-year changes but different mean BMI patterns. CONCLUSIONS: BF levels were higher in South Asian children than in other groups in 2007 and diverged from those in White children until 2013, a pattern not apparent from unadjusted BMI data

Are Ethnic and Gender Specific Equations Needed to Derive Fat Free Mass from Bioelectrical Impedance in Children of South Asian, Black African-Caribbean and White European Origin? Results of the Assessment of Body Composition in Children Study

Background Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat. Methods Cross-sectional study of children aged 8–10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM = linear combination(height+weight+Z); B: FFM = linear combination(height2/Z); C: FFM = linear combination(height2/Z+weight)}. Results Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set. Conclusions Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences

Development and validation of a prediction model for fat mass in children and adolescents: Meta-analysis using individual participant data

© Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to. To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need for more complex forms of assessment. Design Individual participant data meta-analysis. Setting Four population based cross sectional studies and a fifth study for external validation, United Kingdom. Participants A pooled derivation dataset (four studies) of 2375 children and an external validation dataset of 176 children with complete data on anthropometric measurements and deuterium dilution assessments of fat mass. Main outcome measure Multivariable linear regression analysis, using backwards selection for inclusion of predictor variables and allowing non-linear relations, was used to develop a prediction model for fat-free mass (and subsequently fat mass by subtracting resulting estimates from weight) based on the four studies. Internal validation and then internal-external cross validation were used to examine overfitting and generalisability of the model\u27s predictive performance within the four development studies; external validation followed using the fifth dataset. Results Model derivation was based on a multi-ethnic population of 2375 children (47.8% boys, n=1136) aged 4-15 years. The final model containing predictor variables of height, weight, age, sex, and ethnicity had extremely high predictive ability (optimism adjusted R 2: 94.8%, 95% confidence interval 94.4% to 95.2%) with excellent calibration of observed and predicted values. The internal validation showed minimal overfitting and good model generalisability, with excellent calibration and predictive performance. External validation in 176 children aged 11-12 years showed promising generalisability of the model (R 2: 90.0%, 95% confidence interval 87.2% to 92.8%) with good calibration of observed and predicted fat mass (slope: 1.02, 95% confidence interval 0.97 to 1.07). The mean difference between observed and predicted fat mass was -1.29 kg (95% confidence interval -1.62 to -0.96 kg). Conclusion The developed model accurately predicted levels of fat mass in children aged 4-15 years. The prediction model is based on simple anthropometric measures without the need for more complex forms of assessment and could improve the accuracy of assessments for body fatness in children (compared with those provided by body mass index) for effective surveillance, prevention, and management of clinical and public health obesity

Body-mass index adjustments to increase the validity of body fatness assessment in UK black African and South Asian children: a cross-sectional calibration study

BackgroundExcess childhood body fatness, overweightness, and obesity are a major public health challenge in the UK. Accurate assessments, usually based on body-mass index (BMI), are crucial. However, recent studies have demonstrated that BMI underestimates body fatness in South Asian children and overestimates it in black African children. These errors are a concern in these ethnic minority populations, particularly UK South Asians, who are at high risk of obesity, type 2 diabetes, and cardiovascular disease. We aimed to develop BMI adjustments for these children to ensure that BMI relates to body fatness in the same way as for white European children.MethodsFour recent UK population-based studies, which used deuterium dilution assessments of fat mass as a reference method, were pooled to include 1725 children (52% girls) aged 4–12 years (mean 9·3, SD 1·6) of white European, South Asian, and black African origins. A height-standardised fat-mass index (FMI) was derived to represent body fatness. Linear regression models were fitted, separately by sex, to quantify ethnic differences in BMI–FMI associations and to provide ethnic-specific BMI adjustments.FindingsThe FMI derived for this study population and used in analyses was fat mass/height5, which was independent of height for the 4–12-year age-group. BMI consistently underestimated body fatness in South Asians, requiring a BMI adjustment of +1·12 kg/m2 (95% CI 0·83–1·41) for boys and +1·07 (0·74–1·39) for girls, irrespective of age and FMI. BMI overestimated body fatness in black Africans. However, adjustments for black African children were more complex, with statistically significant interactions between black African ethnicity and FMI (p=0·004 boys, p=0·003 girls) and between FMI and age-group (p\u3c0·0001 boys and girls). BMI adjustments therefore varied by age-group and FMI level, between −0·24 and −2·84 kg/m2 for boys and between −0·22 and −2·86 kg/m2 for girls for unadjusted BMI values of 13 kg/m2 in 10–12 year-olds and 25 kg/m2 in 4–6 year-olds, respectively.InterpretationBMI underestimated body fatness in South Asians and overestimated it in black Africans. Ethnic-specific adjustments—increasing BMI in South Asians and reducing BMI in black Africans—can improve the accuracy of body fatness assessment in these children.FundingThis work was supported by the British Heart Foundation (grant ref PG/15/19/31336) and National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (South London) (grant ref CLAHRC-2013-10022). Primary data collection was funded by the British Heart Foundation (PG/11/42/28895), BUPA Foundation (TBF-S09-019), Child Growth Foundation (GR 10/03), and Wellcome Trust (WT094129MA). MF is supported by Great Ormond Street Hospital Childrens\u27 Charity